Summarise new App Store reviews for your product team in Slack

import json
from clickruntime import on_trigger, credentials, http, state, notify, ai

APP_ID, COUNTRY = "1234567890", "us"
HOST, NS = "https://reviews-abc123.svc.aped-1234.pinecone.io", "app-reviews"

def search(text, k=5):
    r = http.post(f"{HOST}/records/namespaces/{NS}/search", json={"query": {"inputs": {"text": text}, "top_k": k}}, headers={
        "Api-Key": credentials.secret("PINECONE_API_KEY"), "X-Pinecone-API-Version": "2025-04"}).json()
    return [h["fields"] for h in r["result"]["hits"]]
def upsert(records):
    http.post(f"{HOST}/records/namespaces/{NS}/upsert", data="\n".join(json.dumps(r) for r in records[:96]), headers={
        "Api-Key": credentials.secret("PINECONE_API_KEY"), "X-Pinecone-API-Version": "2025-04", "Content-Type": "application/x-ndjson"}).raise_for_status()

@on_trigger
def run(event):
    feed = http.get(f"https://itunes.apple.com/{COUNTRY}/rss/customerreviews/id={APP_ID}/sortby=mostrecent/json").json()
    seen = set(state.get("seen") or [])
    new = [e for e in feed["feed"].get("entry", []) if "im:rating" in e and e["id"]["label"] not in seen]
    if not new:
        return {"new": 0}
    texts = [f"{e['im:rating']['label']}★ {e['title']['label']}: {e['content']['label'][:500]}" for e in new]
    upsert([{"_id": e["id"]["label"], "chunk_text": t} for e, t in zip(new, texts)])
    similar = {h["chunk_text"] for t in texts[:5] for h in search(t, 4)} - set(texts)
    summary = ai.generate("Summarise today's app reviews as top complaints and top praise (short bullets). Say which "
                          f"complaints also appear in older reviews.\nTODAY:\n" + "\n".join(texts) + "\nOLDER SIMILAR:\n"
                          + "\n".join(similar), max_output_tokens=500).text
    notify.slack(f"*{len(new)} new App Store reviews*\n{summary}", channel="#product")
    state.set("seen", sorted(seen | {e["id"]["label"] for e in new})[-3000:])
    return {"new": len(new)}